Prediction of thermal conductivity of steels
M. J. Peet, H. S. Hasan and H. K. D. H. Bhadeshia
International Journal of Heat and Mass Transfer, 54 (2011) 2602-2608.
DOI:10.1016/j.ijheatmasstransfer.2011.01.025
Abstract
A model of thermal conductivity as a function of temperature and steel composition has been produced using a neural network technique based upon a Bayesian statistics framework. The model allows the estimation of conductivity for heat transfer problems, along with the appropriate uncertainty. The performance of the model is demonstrated by making predictions of previous experimental results which were not included in the process which leads to the creation of the model.
External Links
- Paper hosted at Phase Transformations website.
- The model used is available for download from the map website.